Abstract
For the first time, we apply a full-scale 3D seismic virtual-source survey (VSS) for the purpose of near-mine mineral exploration. The data was acquired directly above the Kylylahti underground mine in Finland. Recorded ambient noise (AN) data is characterized using power-spectral density (PSD) and beamforming. Data has most energy at frequencies 25–90 Hz and arrivals with velocities higher than 4 km/s have wide range of azimuths. Based on the PSD and beamforming results, we created 10-days subset of AN recordings that were dominated by multi-azimuth high-velocity arrivals. We use illumination-diagnosis technique and location procedure to show that the AN recordings associated with high apparent velocities are related to body-wave events. Next, we produce 994 virtual-source gathers by applying seismic-interferometry processing by cross-correlating AN at all receivers resulting in full 3D VSS. We apply standard 3D time-domain reflection seismic data processing and imaging using both a selectively stacked subset and full passive data, and validate the results against a pre-existing detailed geological information and 3D active-source survey data processed in the same way as the passive data. The resulting post-stack migrated sections show agreement of reflections between the passive and active data and indicate that VSS provide images where the active-source data are not available due to terrain restrictions. We conclude that while the all-noise approach provides some higher quality reflections related to the inner geological contacts within the target formation and the general dipping trend of the formation, the selected subset is most efficient in resolving the base of formation.
Highlights
Ambient noise (AN) seismic interferometry (SI) principles can be used to extract the reflection response of the subsurface at 30 different scales (Daneshvar et al, 1995; Draganov et al, 2009, 2013; Ruigrok et al, 2010; Ryberg, 2011; Quiros et al, 2016).the original derivations of SI, as well as the majority of surface-seismic applications have considered relatively simple geological structures
It was shown that higher frequency (> 10 Hz) body-wave sources generated by trains and cars could be used to image a major dipping layer interpreted as the gabbroic intrusion that hosts Cu-PGE mineralizations 45 in the area, and the extent of which provides crucial information for guiding mineral exploration
On the other hand, stacking all noise represents an attempt of utilizing the full capacity of ANSI by incorporating all body-waves events which occurred during recording time, but were not dominant during the days designated as dominated by surface-wave noise
Summary
Ambient noise (AN) seismic interferometry (SI) principles can be used to extract the reflection response of the subsurface at 30 different scales (Daneshvar et al, 1995; Draganov et al, 2009, 2013; Ruigrok et al, 2010; Ryberg, 2011; Quiros et al, 2016). The methodology adopted in 150 this study builds on these earlier results and can be summarized as follows: (1) General description of the recorded wavefield to identify dominant frequencies, directions of illumination and apparent velocities of the AN sources; (2) Quantification of body-wave energy present in the recorded data using the TWEED approach and obtaining spatial distribution of the noise sources; (3) Actual SI data retrieval, i.e. obtaining VSGs through cross-correlation for the two sets of data: (i) for 10 days when the body-wave events are dominating and (ii) for the full 30 days of data; (4) Standard hardrock reflection seismic processing 155 of the obtained VSGs. The above 4 processing steps together with validation and interpretation of passive results using a direct comparison to an active survey as a benchmark, and to the available detailed geological data and models as a reference, add up to the 5 main processing blocks forming the full-scale 3D seismic VSS methodology for the purpose of near-mine mineral exploration developed in this study (see flowchart, where the gray-gradient-colored blocks in the right column indicate our modifications of the state-of-the-art AN imaging workflow proposed by Draganov et al, 2013)
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